Python optimizers.BestFitOptimization() Examples
The following are 9
code examples of optimizers.BestFitOptimization().
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Example #1
Source File: trainer.py From DOTA_models with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #2
Source File: trainer.py From yolo_v2 with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #3
Source File: trainer.py From Gun-Detector with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #4
Source File: trainer.py From hands-detection with MIT License | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #5
Source File: trainer.py From object_detection_kitti with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #6
Source File: trainer.py From object_detection_with_tensorflow with MIT License | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #7
Source File: trainer.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #8
Source File: trainer.py From models with Apache License 2.0 | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None
Example #9
Source File: trainer.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def get_value_opt(self): if self.value_opt == 'grad': return optimizers.GradOptimization( learning_rate=self.learning_rate, max_iter=5, mix_frac=0.05) elif self.value_opt == 'lbfgs': return optimizers.LbfgsOptimization(max_iter=25, mix_frac=0.1) elif self.value_opt == 'best_fit': return optimizers.BestFitOptimization(mix_frac=1.0) else: return None